A panel of nine cerebrospinal fluid biomarkers may identify patients with atypical parkinsonian syndromes

Abstract

Background: Patients presenting with parkinsonian syndromes share many clinical features, which can make diagnosis difficult. This is important as atypical parkinsonian syndromes (APSs) such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and corticobasal syndrome (CBS) carry a poor prognosis, compared with patients with Parkinson's disease (PD). In addition, there is overlap between APS and dementia diseases, such as Alzheimer's disease (AD) and frontotemporal dementia (FTD).

Objective: To use a panel of cerebrospinal fluid (CSF) biomarkers to differentiate patients with APS from PD and dementia.

Methods: A prospective cohort of 160 patients and 30 control participants were recruited from a single specialist centre. Patients were clinically diagnosed according to current consensus criteria. CSF samples were obtained from patients with clinical diagnoses of PD (n=31), PSP (n=33), CBS (n=14), MSA (n=31), AD (n=26) and FTD (n=16). Healthy, elderly participants (n=30) were included as controls. Total τ (t-τ), phosphorylated τ (p-τ), β-amyloid 1-42 (Aβ42), neurofilament light chain (NFL), α-synuclein (α-syn), amyloid precursor protein soluble metabolites α and β (soluble amyloid precursor protein (sAPP)α, sAPPβ) and two neuroinflammatory markers (monocyte chemoattractant protein-1 and YKL-40) were measured in CSF. A reverse stepwise regression analysis and the false discovery rate procedure were used.

Results: CSF NFL (p<0.001), sAPPα (p<0.001) and a-syn (p=0.003) independently predicted diagnosis of PD versus APS. Together, these nine biomarkers could differentiate patients with PD from APS with an area under the curve of 0.95 and subtypes of APS from one another. There was good discriminatory power between parkinsonian groups, dementia disorders and healthy controls.

Conclusions: A panel of nine CSF biomarkers was able to differentiate APS from patients with PD and dementia. This may have important clinical utility in improving diagnostic accuracy, allowing better prognostication and earlier access to potential disease-modifying therapies.

Keywords: CORTICOBASAL DEGENERATION; CSF; PARKINSON'S DISEASE; POST MORTEM; SUPRANUCLEAR PALSY.

Figure 1

Box plots showing levels of biomarkers in parkinsonian conditions, dementia disorders and healthy controls. Levels of CSF biomarkers in the different diagnostic groups. Box plots of t-τ, p-τ, Aβ42, α-syn, NFL, YKL-40, MCP-1, sAPPα and sAPPβ. The lower, upper and middle lines of boxes correspond to the 25th centile, 75th centile and median, respectively. The whiskers at the top and bottom extend from the 5th to the 95th centiles, respectively, and the dots represent outliers. CSF, cerebrospinal fluid; PSP, progressive supranuclear palsy; CBS, corticobasal syndrome; MSA, multiple system atrophy; PD, Parkinson’s disease; AD, Alzheimer’s disease; FTD, frontotemporal dementia; t-τ, total τ; p-τ, phosphorylated τ; Aβ42, amyloid β 42; α-syn, α-synuclein; NFL, neurofilament light chain; YKL-40, tyrosine (Y), lysine (K) and leucine (L) 40 kDa; MCP-1, monocyte chemoattractant protein-1; sAPPα, soluble amyloid precursor protein α; sAPPβ, soluble amyloid precursor protein β.

Figure 2

ROC curves showing the three most discriminatory analytes (NFL, sAPPα and α-syn) and two nuisance covariates (disease duration and severity) differentiating PD from APS. (A) Individual ROC curves performed to examine the relationship between diagnostic sensitivity and specificity for the three most discriminatory analytes and two nuisance covariates when differentiating PD from APS. (B) Multivariate discriminant analysis was used to study diagnostic accuracy when the three most discriminatory analytes and two nuisance covariates were studied simultaneously producing a single ROC curve for the diagnostic accuracy of PD versus APS. ROC, receiver operating characteristic; PD, Parkinson’s disease; APS, atypical parkinsonian symdrome; α-syn, α-synuclein; NFL, neurofilament light chain; sAPPα, soluble amyloid precursor protein α; HY score, Hoehn and Yahr score of disease severity.

Figure 3

ROC curves showing NFL and age, and the combination of the two differentiating PSP from MSA. (A) Individual ROC curves performed to examine the relationship between diagnostic sensitivity and specificity CSF NFL, and age when differentiating PSP from MSA. (B) Multivariate discriminant analysis was used to study diagnostic accuracy when NFL and age were both studied simultaneously producing a single ROC curve for the diagnostic accuracy of PSP versus MSA. PSP, progressive supranuclear palsy; MSA, multiple system atrophy; ROC, receiver operating characteristic; CSF, cerebrospinal fluid; NFL, neurofilament light chain.

Figure 4

ROC curves showing the combination of all nine analytes differentiating all parkinsonian groups from healthy controls and dementia disorders. (A) ROC curve combining all nine analytes to show the diagnostic accuracy of parkinsonian groups (PD, PSP, CBS, MSA) and healthy controls. (B) ROC curve combining all nine analytes to show the diagnostic accuracy of parkinsonian groups (PD, PSP, CBS, MSA) and dementia disorders (AD and FTD). ROC, receiver operating characteristic; PD, Parkinson’s disease; PSP, progressive supranuclear palsy; CBS, corticobasal syndrome; MSA, multiple system atrophy; AD, Alzheimer’s disease; FTD, frontotemporal dementia.